#include <iostream>
#include <string>
#include <list>
#include <vector>
#include <map>
#include <stack>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace std;
using namespace cv;
//------------------------------【两步法新改进版】----------------------------------------------
// 对二值图像进行连通区域标记,从1开始标号
void Two_PassNew( const Mat &bwImg, Mat &labImg )
{
assert( bwImg.type()==CV_8UC1 );
labImg.create( bwImg.size(), CV_32SC1 ); //bwImg.convertTo( labImg, CV_32SC1 );
labImg = Scalar(0);
labImg.setTo( Scalar(1), bwImg );
assert( labImg.isContinuous() );
const int Rows = bwImg.rows - 1, Cols = bwImg.cols - 1;
int label = 1;
vector<int> labelSet;
labelSet.push_back(0);
labelSet.push_back(1);
//the first pass
int *data_prev = (int*)labImg.data; //0-th row : int* data_prev = labImg.ptr<int>(i-1);
int *data_cur = (int*)( labImg.data + labImg.step ); //1-st row : int* data_cur = labImg.ptr<int>(i);
for( int i = 1; i < Rows; i++ )
{
data_cur++;
data_prev++;
for( int j=1; j<Cols; j++, data_cur++, data_prev++ )
{
if( *data_cur!=1 )
continue;
int left = *(data_cur-1);
int up = *data_prev;
int neighborLabels[2];
int cnt = 0;
if( left>1 )
neighborLabels[cnt++] = left;
if( up > 1)
neighborLabels[cnt++] = up;
if( !cnt )
{
labelSet.push_back( ++label );
labelSet[label] = label;
*data_cur = label;
continue;
}
int smallestLabel = neighborLabels[0];
if( cnt==2 && neighborLabels[1]<smallestLabel )
smallestLabel = neighborLabels[1];
*data_cur = smallestLabel;
// 保存最小等价表
for( int k=0; k<cnt; k++ )
{
int tempLabel = neighborLabels[k];
int& oldSmallestLabel = labelSet[tempLabel]; //这里的&不是取地址符号,而是引用符号
if( oldSmallestLabel > smallestLabel )
{
labelSet[oldSmallestLabel] = smallestLabel;
oldSmallestLabel = smallestLabel;
}
else if( oldSmallestLabel<smallestLabel )
labelSet[smallestLabel] = oldSmallestLabel;
}
}
data_cur++;
data_prev++;
}
//更新等价队列表,将最小标号给重复区域
for( size_t i = 2; i < labelSet.size(); i++ )
{
int curLabel = labelSet[i];
int prelabel = labelSet[curLabel];
while( prelabel != curLabel )
{
curLabel = prelabel;
prelabel = labelSet[prelabel];
}
labelSet[i] = curLabel;
}
//second pass
data_cur = (int*)labImg.data;
for( int i = 0; i < Rows; i++ )
{
for( int j = 0; j < bwImg.cols-1; j++, data_cur++)
*data_cur = labelSet[ *data_cur ];
data_cur++;
}
}
//-------------------------------【老版两步法】-------------------------------------------
void Two_PassOld(const cv::Mat& _binImg, cv::Mat& _lableImg)
{
//connected component analysis (4-component)
//use two-pass algorithm
//1. first pass: label each foreground pixel with a label
//2. second pass: visit each labeled pixel and merge neighbor label
//
//foreground pixel: _binImg(x,y) = 1
//background pixel: _binImg(x,y) = 0
if(_binImg.empty() || _binImg.type() != CV_8UC1)
{
return;
}
// 1. first pass
_lableImg.release();
_binImg.convertTo(_lableImg, CV_32SC1 );
int label = 1; // start by 2
std::vector<int> labelSet;
labelSet.push_back(0); //background: 0
labelSet.push_back(1); //foreground: 1
int rows = _binImg.rows - 1;
int cols = _binImg.cols - 1;
for( int i = 1; i < rows; i++)
{
int* data_preRow = _lableImg.ptr<int>(i-1);
int* data_curRow = _lableImg.ptr<int>(i);
for(int j = 1; j < cols; j++)
{
if(data_curRow[j] == 1)
{
std::vector<int> neighborLabels;
neighborLabels.reserve(2); //reserve(n) 预分配n个元素的存储空间
int leftPixel = data_curRow[j-1];
int upPixel = data_preRow[j];
if( leftPixel > 1)
{
neighborLabels.push_back(leftPixel);
}
if( upPixel > 1)
{
neighborLabels.push_back(upPixel);
}
if(neighborLabels.empty())
{
labelSet.push_back(++label); //assign to a new label
data_curRow[j] = label;
labelSet[label] = label;
}
else
{
std::sort(neighborLabels.begin(),neighborLabels.end());
int smallestLabel = neighborLabels[0];
data_curRow[j] = smallestLabel;
//save equivalence
for(size_t k = 1; k < neighborLabels.size();k++)
{
int tempLabel = neighborLabels[k];
int& oldSmallestLabel = labelSet[tempLabel];
if(oldSmallestLabel > smallestLabel)
{
labelSet[oldSmallestLabel] = smallestLabel;
oldSmallestLabel = smallestLabel;
}
else if(oldSmallestLabel < smallestLabel)
{
labelSet[smallestLabel] = oldSmallestLabel;
}
}
}
}
}
}
//update equivalent labels
//assigned with the smallest label in each equivalent label set
for(size_t i = 2; i < labelSet.size();i++)
{
int curLabel = labelSet[i];
int prelabel = labelSet[curLabel];
while (prelabel != curLabel )
{
curLabel = prelabel;
prelabel = labelSet[prelabel];
}
labelSet[i] = curLabel;
}
//2. second pass
for( int i = 0; i < rows; i++ )
{
int *data = _lableImg.ptr<int>(i);
for(int j = 0; j < cols; j++ )
{
int& pixelLabel = data[j];
pixelLabel = labelSet[pixelLabel];
}
}
}
//---------------------------------【种子填充法老版】-------------------------------
void SeedFillOld(const cv::Mat& binImg, cv::Mat& lableImg) //种子填充法
{
// 4邻接方法
if (binImg.empty() ||
binImg.type() != CV_8UC1)
{
return;
}
lableImg.release();
binImg.convertTo(lableImg, CV_32SC1);
int label = 1;
int rows = binImg.rows - 1;
int cols = binImg.cols - 1;
for (int i = 1; i < rows-1; i++)
{
int* data= lableImg.ptr<int>(i);
for (int j = 1; j < cols-1; j++)
{
if (data[j] == 1)
{
std::stack<std::pair<int,int>> neighborPixels;
neighborPixels.push(std::pair<int,int>(i,j)); // 像素位置: <i,j>
++label; // 没有重复的团，开始新的标签
while (!neighborPixels.empty())
{
std::pair<int,int> curPixel = neighborPixels.top(); //如果与上一行中一个团有重合区域，则将上一行的那个团的标号赋给它
int curX = curPixel.first;
int curY = curPixel.second;
lableImg.at<int>(curX, curY) = label;
neighborPixels.pop();
if (lableImg.at<int>(curX, curY-1) == 1)
{//左边
neighborPixels.push(std::pair<int,int>(curX, curY-1));
}
if (lableImg.at<int>(curX, curY+1) == 1)
{// 右边
neighborPixels.push(std::pair<int,int>(curX, curY+1));
}
if (lableImg.at<int>(curX-1, curY) == 1)
{// 上边
neighborPixels.push(std::pair<int,int>(curX-1, curY));
}
if (lableImg.at<int>(curX+1, curY) == 1)
{// 下边
neighborPixels.push(std::pair<int,int>(curX+1, curY));
}
}
}
}
}
}
//-------------------------------------------【种子填充法新版】---------------------------
void SeedFillNew(const cv::Mat& _binImg, cv::Mat& _lableImg )
{
// connected component analysis(4-component)
// use seed filling algorithm
// 1. begin with a forgeground pixel and push its forground neighbors into a stack;
// 2. pop the pop pixel on the stack and label it with the same label until the stack is empty
//
// forground pixel: _binImg(x,y)=1
// background pixel: _binImg(x,y) = 0
if(_binImg.empty() ||
_binImg.type()!=CV_8UC1)
{
return;
}
_lableImg.release();
_binImg.convertTo(_lableImg,CV_32SC1);
int label = 0; //start by 1
int rows = _binImg.rows;
int cols = _binImg.cols;
Mat mask(rows, cols, CV_8UC1);
mask.setTo(0);
int *lableptr;
for(int i=0; i < rows; i++)
{
int* data = _lableImg.ptr<int>(i);
uchar *masKptr = mask.ptr<uchar>(i);
for(int j = 0; j < cols; j++)
{
if(data[j] == 255&&mask.at<uchar>(i,j)!=1)
{
mask.at<uchar>(i,j)=1;
std::stack<std::pair<int,int>> neighborPixels;
neighborPixels.push(std::pair<int,int>(i,j)); // pixel position: <i,j>
++label; //begin with a new label
while(!neighborPixels.empty())
{
//get the top pixel on the stack and label it with the same label
std::pair<int,int> curPixel =neighborPixels.top();
int curY = curPixel.first;
int curX = curPixel.second;
_lableImg.at<int>(curY, curX) = label;
//pop the top pixel
neighborPixels.pop();
//push the 4-neighbors(foreground pixels)
if(curX-1 >= 0)
{
if(_lableImg.at<int>(curY,curX-1) == 255&&mask.at<uchar>(curY,curX-1)!=1) //leftpixel
{
neighborPixels.push(std::pair<int,int>(curY,curX-1));
mask.at<uchar>(curY,curX-1)=1;
}
}
if(curX+1 <=cols-1)
{
if(_lableImg.at<int>(curY,curX+1) == 255&&mask.at<uchar>(curY,curX+1)!=1)
// right pixel
{
neighborPixels.push(std::pair<int,int>(curY,curX+1));
mask.at<uchar>(curY,curX+1)=1;
}
}
if(curY-1 >= 0)
{
if(_lableImg.at<int>(curY-1,curX) == 255&&mask.at<uchar>(curY-1,curX)!=1)
// up pixel
{
neighborPixels.push(std::pair<int,int>(curY-1, curX));
mask.at<uchar>(curY-1,curX)=1;
}
}
if(curY+1 <= rows-1)
{
if(_lableImg.at<int>(curY+1,curX) == 255&&mask.at<uchar>(curY+1,curX)!=1)
//down pixel
{
neighborPixels.push(std::pair<int,int>(curY+1,curX));
mask.at<uchar>(curY+1,curX)=1;
}
}
}
}
}
}
}
//---------------------------------【颜色标记程序】-----------------------------------
//彩色显示
cv::Scalar GetRandomColor()
{
uchar r = 255 * (rand()/(1.0 + RAND_MAX));
uchar g = 255 * (rand()/(1.0 + RAND_MAX));
uchar b = 255 * (rand()/(1.0 + RAND_MAX));
return cv::Scalar(b,g,r);
}
void LabelColor(const cv::Mat& labelImg, cv::Mat& colorLabelImg)
{
int num = 0;
if (labelImg.empty() ||
labelImg.type() != CV_32SC1)
{
return;
}
std::map<int, cv::Scalar> colors;
int rows = labelImg.rows;
int cols = labelImg.cols;
colorLabelImg.release();
colorLabelImg.create(rows, cols, CV_8UC3);
colorLabelImg = cv::Scalar::all(0);
for (int i = 0; i < rows; i++)
{
const int* data_src = (int*)labelImg.ptr<int>(i);
uchar* data_dst = colorLabelImg.ptr<uchar>(i);
for (int j = 0; j < cols; j++)
{
int pixelValue = data_src[j];
if (pixelValue > 1)
{
if (colors.count(pixelValue) <= 0)
{
colors[pixelValue] = GetRandomColor();
num++;
}
cv::Scalar color = colors[pixelValue];
*data_dst++ = color[0];
*data_dst++ = color[1];
*data_dst++ = color[2];
}
else
{
data_dst++;
data_dst++;
data_dst++;
}
}
}
printf("color num : %d \n", num );
}
//------------------------------------------【测试主程序】-------------------------------------
int main()
{
cv::Mat binImage = cv::imread("ltc2.jpg", 0);
//这里必须要有,当背景为黑色时
cv::threshold(binImage, binImage, 50, 1, CV_THRESH_BINARY);
//当背景为白色时
//cv::threshold(src, src, 50, 1, THRESH_BINARY_INV);
cv::Mat labelImg;
double time;
time= getTickCount();
//对应四种方法，需要哪一种，则调用哪一种
//Two_PassOld(binImage, labelImg);
//Two_PassNew(binImage, labelImg);
//当使用老版种子填充法时，如果边界上存在连通域，需要在边界上padding,否则会溢出
//Mat pad;
//copyMakeBorder(binImage,pad,1,1,1,1,BORDER_CONSTANT,0);
//SeedFillOld(pad, labelImg);
//新版种子填充法注意把代码中的255改为0;
//SeedFillNew(binImage, labelImg);
time = 1000*((double)getTickCount() - time)/getTickFrequency();
cout<<std::fixed<<time<<"ms"<<endl;
//彩色显示
cv::Mat colorLabelImg;
LabelColor(labelImg, colorLabelImg);
cv::imshow("colorImg", colorLabelImg);
//灰度显示
cv::Mat grayImg;
labelImg *= 10;
labelImg.convertTo(grayImg, CV_8UC1);
cv::imshow("labelImg", grayImg);
double minval, maxval;
minMaxLoc(labelImg,&minval,&maxval);
cout<<"minval"<<minval<<endl;
cout<<"maxval"<<maxval<<endl;
cv::waitKey(0);
return 0;
}
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